Mathematical Modelling of Magnetic Abrasive Machining Hybrid Operation: A Review

الانهاء بالحث الممغنط هو طريقة انهاء سطحي غير تقليدي لإنتاج اجزاء ذات نوعية عالية والتي يسيطر عليها بالطاقة المغناطيسية. طورت عملية الحك الممغنط بعض الخواص الميكانيكية للسطح. بعض طرق الانهاء السطحي التقليدية مثل تنعيم السطح الداخلي، التجليخ والتنعيم الخارجي بدلت الان بهذه الطريقة. في هذا البحث (مراجعة) سنتناول بالتفصيل اساس عملية الانهاء بالحث الممغنط، متغيرات العملية وتأثيرها على المخرجات (الاستجابة)، نمذجة العملية وتطورها للسطوح المستقيمة. اضافة الى ذلك هناك نوع جديد من الانهاء بالحث الممغنط المندمج مع التشغيل الكهروكيمياوي لإنتاج التشغيل بالحك الممغنط الكهروكيمياوي. اداء النموذج الرياضي والامثلية المتعددة لتنبأ المخرجات مثل معدل الازالة المعدنية، الانهاء السطحي والمنطقة المتأثرة بالحرارة.... الخ وجدت للمقارنة بدلالة دقة وسرع التنبؤ.   Magnetic Abrasive Finishing (MAF) or super finishing is a modern unconventional finishing technique to produce high quality of parts, which is controlled by a magnetic energy. Magnetic abrasive operation develops some of the mechanical properties such as the surface quality. Nowadays, many of the traditional finishing technique such as honing, polishing and grinding are now being replaced by this process. In this review, principles of the MAF process, processing factors and their influence on the responses, the process modeling and development of the MAF method for flat surfaces will be examined in details research work in the literature. Additionally, there is a new type of MAF connected with Electrochemical Machining (ECM) to produce Electrochemical Magnetic Abrasive Machining (EMAM). The performance of models and multi-optimizing for predicting the responses such as metal removal rate (MRR), surface finish (SF), heat affected zone (HAZ) etc. are found to comparable in terms of the prediction accuracy and speed. &nbsp

The Detection of Students' Abnormal Behavior in Online Exams Using Facial Landmarks in Conjunction with the YOLOv5 Models

The popularity of massive open online courses (MOOCs) and other forms of distance learning has increased recently. Schools and institutions are going online to serve their students better. Exam integrity depends on the effectiveness of proctoring remote online exams. Proctoring services powered by computer vision and artificial intelligence have also gained popularity. Such systems should employ methods to guarantee an impartial examination. This research demonstrates how to create a multi-model computer vision system to identify and prevent abnormal student behaviour during exams. The system uses You only look once (YOLO) models and Dlib facial landmarks to recognize faces, objects, eye, hand, and mouth opening movement, gaze sideways, and use a mobile phone. Our approach offered a model that analyzes student behaviour using a deep neural network model learned from our newly produced dataset" StudentBehavioralDS." On the generated dataset, the "Behavioral Detection Model" had a mean Average Precision (mAP) of 0.87, while the "Mouth Opening Detection Model" and "Person and Objects Detection Model" had accuracies of 0.95 and 0.96, respectively. This work demonstrates good detection accuracy. We conclude that using computer vision and deep learning models trained on a private dataset, our idea provides a range of techniques to spot odd student behaviour during online tests

Postoperative cognitive dysfunction following general anaesthesia in patients undergoing elective non-cardiac surgery

Objective: To determine frequency of early postoperative cognitive dysfunction (POCD) in patients aged 40 to 60 years, following general anaesthesia in patients undergoing elective, non-cardiac surgery.Study design: Descriptive study.Place and duration of study: Department of Anaesthesiology, The Aga Khan University Hospital (AKUH), Karachi, from December 2015 to May 2016.Methodology: After obtaining approval from Ethical Review Committee of AKUH and informed consent, ASA I and II patients, aged between 40 to 60 years of either gender, undergoing general anaesthesia for elective non-cardiac surgical procedures, were recruited. Patients were assessed preoperatively by using mini-mental state examination (MMSE); and patients having a score equal to or greater than 23 (maximum 30) were included in the study. All patients were reassessed at 24 hours postoperatively by MMSE. Both the MMSE evaluations were performed by primary investigator on predesigned data collection form.Results: A total of 150 patients were enrolled in the study. Preoperative MMSE score ranged from 24 to 30 while postoperative MMSE score (at 24 hours) was between 25 and 30. Thus, no patient developed POCD following general anaesthesia for elective, non-cardiac surgery in this study.Conclusion: Early POCD was not found in the presently studied population of middle aged patients having elective non-cardiac surgery under general anaesthesia. Key Words: Postoperative cognitive dysfunction (POCD), General anaesthesia, Non-cardiac surgery, Mini- mental state examination

Optimization of Friction Stir Welding Parameters of Al 6061 and Al 7075 Using GRA

لحام الخلط الاحتكاكي هو تكنولوجيا واعدة لربط سبائك الألومنيوم غير المتشابهة. سبائك الالمنيوم تستخدم بصورة شائعة في صناعات الفضاء مثل ابدان الطائرات والالواح والأجنحة نظرا لمتانته العالية نسبه الى وزنه. لذلك هنالك محاوله للوصول الى أمثليه متغيرات عمليه اللحام الاحتكاكي عند لحام سبيكتين من الالمنيوم هما6061 و7075 باستخدام برنامجMinitab 16  من اجل تحسين خصائص الشد مثل اجهاد الخضوع (YS) ومتانة الشد القصوى(UTS) ونسبة الاستطالة(E) . طريقه Taguchi استخدمت كأساس لتحليل العلاقة الرمادية (GRA) باستخدام عاملين هما سرعه دوران الاداة (TRS) وسرعه اللحام (WS بأربع مستويات. النتائج اظهرت ان المتغيرات التي هي سرعه دوران الاداة وسرعه اللحام لها تأثير كبير على اجهاد الخضوع ومتانة الشد القصوى ونسبة الاستطالة. كما اظهرت النتائج ان طريقه Taguchi المستخدمة كأساس لتحليل العلاقة الرمادية تحسن المخرجات لسبيكتي الالمنيوم 6061 7075 الملحومتان.Friction stir welding (FSW) is proved as a promising welding technology for joining dissimilar aluminium alloys. Aluminium alloys are used extensively within the aerospace industry for applications such as fuselage and wing skin panels due to their high strength to weight ratio. Therefore, an effort is made to optimize the process parameters of FSW using Al 6061 and Al 7075 alloys by the Minitab 16 program in order to enhance  tensile properties such as elongation (E), yield stress (YS), and ultimate tensile strength (UTS). Grey relational analysis (GRA) based on the Taguchi method is applied using two factors tool rotational speeds (TRS) and welding speed (WS) with four levels. Results show that the variables, namely the tool rotation speed and welding speed have a significant effect on yield stress, ultimate tensile strength and elongation. Results also show that the Taguchi based grey relational approach improved properties of output response of welded Al 6061 and Al 7075 aluminum alloys

APACHE-II Score Correlation With Mortality And Length Of Stay In An Intensive Care Unit

Objective: To correlate the APACHE-II score system with mortality and length of stay in ICU. Study Design: Cohort study. Place and Duration of Study: The Intensive Care Unit (ICU) of the Aga Khan University Hospital, Karachi, from May 2005 to May 2006. Methodology: All adult patients who were admitted in the ICU were included. APACHE-II score was calculated at the second and seventh days of admission in the ICU. Patients who were discharged alive from the ICU or died after first APACHE-II Score (at 2nd day) were noted as the primary outcome measurement. Second APACHE-II score (at 7th day) was used to predict the length of stay in the ICU. Pearson\u27s correlation coefficient (r) was determined with significance at p \u3c 0.05. Results: In the lowest score category 3-10, 27 out of 30 patients (90%) were discharged and only 3 (10%) died. Out of those 39 patients whose APACHE-II score was found in high category 31 - 40, 33 (84.6%) deaths were observed. This revealed that there might be more chances of death in case of high APACHE-II score (p=0.001). Insignificant but an inverse correlation (r = -0.084, p \u3c 0.183) was observed between APACHE-II score and length of ICU stay. Conclusion: The APACHE-II scoring system was found useful for classifying patients according to their disease severity. There was an inverse relationship between the high score and the length of stay as well higher chances of mortality

Chemi-mechanical pulping of durian rinds

The physical, optical and mechanical characteristics of pulp and paper made from waste durian rinds as an alternative raw material for papermaking were investigated according to TAPPI and MS ISO standards. The durian rinds pulp was produced through chemi-mechanical pulping (CMP). Naturally dried durian rinds were treated with 10% Sodium Hydroxide (NaOH) based on oven dry (o.d) weight of durian rinds in room temperature for 2 hours and pulped by the refiner mechanical pulping (RMP) process. Experimental results show that durian rinds have great potential characteristics as newly explored non-wood based raw material for pulp and paper industry

Sentimental classification analysis of polarity multi-view textual data using data mining techniques

The data and information available in most community environments is complex in nature. Sentimental data resources may possibly consist of textual data collected from multiple information sources with different representations and usually handled by different analytical models. These types of data resource characteristics can form multi-view polarity textual data. However, knowledge creation from this type of sentimental textual data requires considerable analytical efforts and capabilities. In particular, data mining practices can provide exceptional results in handling textual data formats. Besides, in the case of the textual data exists as multi-view or unstructured data formats, the hybrid and integrated analysis efforts of text data mining algorithms are vital to get helpful results. The objective of this research is to enhance the knowledge discovery from sentimental multi-view textual data which can be considered as unstructured data format to classify the polarity information documents in the form of two different categories or types of useful information. A proposed framework with integrated data mining algorithms has been discussed in this paper, which is achieved through the application of X-means algorithm for clustering and HotSpot algorithm of association rules. The analysis results have shown improved accuracies of classifying the sentimental multi-view textual data into two categories through the application of the proposed framework on online polarity user-reviews dataset upon a given topics

Novel expression of microRNAs in serum samples of Iraqi breast cancer women

Although a lot of hard work against cancer to reduces its spread but it still continues to kill with abandon. The need for a biomarker for cancer early detection becomes the most mind concentrated scientists. MicroRNAs the tiny non coding RNA molecules opened new path for the scientists to determine the cancer in its early stages. Expression of microRNAs profiles has been investigated to be involved in cancer development. Here we determined the expression of microRNAs in serum of Iraqi healthy volunteers and other women diagnosed with breast cancer. MicroRNAs expression has been determined by using real time qPCR and delta method has been used. Four of thirteen microRNAs were shown to be expressed in serum of Iraqi breast cancer women. Let-7a and miR-21 were shown to be significantly over expressed in serum of breast cancer compared with healthy serum volunteers (P= 0.022 and 0.026) respectively. While miR-26b and miR-429 found to be significantly down expressed in serum of breast cancer women (P= 0.0034 and 0.031) respectively. The result concluded that these expressed microRNAs in serum of breast cancer women could be used as a first indicator of breast cancer occurrence

Optimization of Cutting Condition for Turning Operation Based On the Taguchi Method

البحث الحالي هو محاولة لنمذجة ظروف القطع في عملية الخراطة باستخدام طريقة تاكوشي وتصميم التجارب. المخرجات (الاستجابة) كانت فقط خشونة السطح. استخدم الفولاذ المقاوم للصدأ AISI 316 SS كمادة مشغلة واختيرت سرعة القطع، معدل التغذية، عمق القطع ونصف قطر رأس العدة كظروف للقطع. استخدمت المصفوفة العمودية القياسية L18 لتصميم التجارب. حللت النتائج التي تم الحصول عليها باسخدام البرنامج Minitab16. نفذ تحليل التباين ANOVA لايجاد العوامل المؤثرة على خشونة السطح. حسبت القيم المستحصلة كاستجابة باستخدام صيغ رياضية وتم تاكيدها بواسطة اختبار التاكيد. من النتائج العملية نلاحظ ان معدل التغذية له التاثير الاكبر على قيم الخشونة متبوعا بسرعة القطع ونصف قطر رأس العدة وعمق القطع.Present dissertation work has attempted to optimize the various significant cutting conditions for turning process by Taguchi method and design of experiments. The response variable is surface roughness (Ra). The stainless steel AISI 316 SS has been used as a workpiece material. The various cutting conditions selected for the study were cutting speed, feed rate, depth of cut and nose radius. A standard L18 orthogonal array was selected for design of experiments. The results obtained from the experimental runs were analyzed using Minitab16 software. Analysis of Variance (ANOVA) for Signal-to-noise (S/N) ratio was done to find the most contributing cutting conditions affecting the Ra. The corresponding values of the response parameter were also calculated using mathematical formulae and confirmed by performing validation experimentation. From the present experimental study, it is observed that Ra in turning process is mainly affected by all input parameters. Feed rate was the most significant factor affecting the Ra followed by cutting speed, nose radius and depth of cut

Implement DNN technology by using wireless sensor network system based on IOT applications

The smart Internet of Things-based system suggested in this research intends to increase network and application accuracy by controlling and monitoring the network. This is a deep learning network. The invisible layer's structure permits it to learn more. Improved quality of service supplied by each sensor node thanks to element-modified deep learning and network buffer capacity management. A customized deep learning technique can be used to train a system that can focus better on tasks. The researchers were able to implement wireless sensor calculations with 98.68 percent precision and the fastest execution time. With a sensor-based system and a short execution time, this article detects and classifies the proxy with 99.21 percent accuracy. However, we were able to accurately detect and classify intrusions and real-time proxy types in this study, which is a significant improvement over previous research